dynatrace-for-ai

Instruments an existing Android project (Kotlin or Java) with the Dynatrace Mobile Agent for basic monitoring. Covers zero-to-first-event setup only: Gradle plugin, agent config, and user privacy opt-in. Do not use for advanced Dynatrace configuration beyond initial instrumentation.

Integrate the Dynatrace Flutter Plugin into a Flutter project — dependency setup, config, SDK bootstrap, navigation tracking, and verification. Trigger: "add Dynatrace to Flutter", "Flutter plugin setup", "instrument Flutter app", "integrate Dynatrace Flutter", "mobile observability Flutter", "dynatrace_flutter_plugin". Do NOT use for: querying Flutter RUM data (use dt-obs-frontends), non-Flutter mobile setups, or Dynatrace server-side configuration.

Real User Monitoring (RUM) on Dynatrace — web and mobile frontends. Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, and frontend-backend linking. Query via `user.events`, `user.sessions`, and `dt.frontend.*` metrics. Does NOT cover synthetic monitoring (HTTP/browser/network checks) — that's a separate domain.

Set up the Dynatrace iOS SDK (OneAgent) in an iOS project using Swift Package Manager. Automates adding the SPM dependency, creating a Dynatrace.plist configuration file, adding the import statement, adding privacy opt-in code, and building the project. Use this skill when the user wants to integrate, install, add, or set up Dynatrace monitoring in their iOS app. Keywords: Dynatrace, iOS, SDK, OneAgent, setup, install, integrate, SPM, Swift Package Manager, Info.plist, DTXApplicationID, DTXBeaconURL, mobile monitoring, RUM.

Kubernetes cluster, pod, node, and workload monitoring. Use when analyzing K8s health, resource optimization, pod failures, OOMKills, scheduling, or security posture. Also use for Kubernetes operational events like pod restarts, OOM events, evictions, and cluster event history. Trigger: "Kubernetes pods", "K8s cluster health", "OOMKill", "pod restarts", "container CPU", "namespace resource usage", "over-provisioned pods", "privileged containers", "pod placement", "K8s node capacity", "running containers by cluster", "workload scheduling", "pod evictions", "K8s labels and annotations", "kubernetes events", "pod restart events", "OOM events", "K8s event history". Do NOT use for explaining existing queries, product documentation questions, AWS-specific resource queries, service-level RED metrics, distributed tracing, or log analysis — use the relevant skill instead.

Integrate the Dynatrace React Native Plugin into a React Native or Expo project — dependency setup, dynatrace.config.js, Babel registration, npx instrumentation, navigation tracking, user privacy options, and verification. Handles both bare React Native and Expo (babel-preset-expo) Babel configuration automatically. Trigger: "add Dynatrace to React Native", "React Native plugin setup", "instrument React Native app", "integrate Dynatrace RN", "mobile observability React Native", "react-native-plugin", "dynatrace react native", "add Dynatrace to Expo", "instrument Expo app", "Dynatrace Expo setup". Do NOT use for: querying RN RUM data (use dt-obs-frontends), non-React Native mobile setups, or Dynatrace server-side configuration.

Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, and entity-level cost drill-down (RUM, hosts, synthetic, K8s). Also directs licensing/entitlement eligibility questions to the right resource (entitlement data is NOT available via DQL). USE ONLY when the user wants to query or analyze their own tenant's actual consumption numbers. Do NOT use for conceptual or 'explain' questions about how DPS billing works, how costs are calculated, what units/weights/the rate card mean, or pricing mechanics — those need no tenant data and belong to Dynatrace documentation, not this skill.

Dynatrace Security Insights for querying and analyzing security data in `security.events`: Runtime Vulnerability Analytics (RVA — third-party + code-level), Runtime Application Protection (RAP), Automated Detections (with MITRE ATT&CK), Security Posture Management — KSPM (CIS/DORA/NIST/STIG) and CSPM/VSPM (PCI/ISO/HIPAA/GDPR) — plus externally ingested security events from third-party products and tools. Covers vulnerability finding/scan events, detection finding events, compliance finding/scan events, and runtime entity contextualization of security findings. Use when asked: "show me open critical vulnerabilities", "which vulnerable functions are in use and publicly exposed?", "top vulnerable libraries / K8s workloads", "what new vulnerabilities appeared in the last 24h?", "what's our CIS/DORA compliance pass rate?", "show SQL injection detections", "map external findings to K8s workloads", "which hosts are not covered by vulnerability scanning?", "cross-provider critical findings summary".

End-to-end Dynatrace alerting lifecycle — anomaly detector setup and model selection (static threshold, adaptive baseline, seasonal baseline), alert event storage in Grail, problem grouping and denoising by root cause analysis, and workflow-based notification routing (email, Slack, ServiceNow, webhook). Use when configuring alerting, choosing between detector types, querying alert event history, understanding why alerts merged into a problem, or setting up problem-triggered notifications.

Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.

Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, and visualizations.

Core DQL syntax rules, common pitfalls, and query patterns. Load this skill when you need to write, build, or fix a DQL query — it prevents syntax errors and guides correct usage. Covers fetch commands, data models, field namespaces, time alignment, entity patterns, metric discovery, and smartscape topology navigation. Trigger: "write a DQL query", "build me a query", "DQL syntax", "how do I query logs/spans/metrics in Dynatrace", "create a timeseries", "fix my DQL", "fetch logs", "smartscapeNodes", "query optimization". Do NOT use for explaining an existing query or answering Dynatrace product questions — those do not require query-construction guidance.

Dynatrace server-side JS runtime — function contract, runtime limits, Web APIs, Node.js modules, fetch with credential vault, and the @dynatrace-sdk/* catalog.

Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.

AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, generic host CPU/memory metrics (use dt-obs-hosts), application-level tracing (use dt-obs-tracing), or log analysis (use dt-obs-logs).

Host and process metrics including CPU, memory, disk, network, containers, and process-level telemetry. Use when analyzing infrastructure health, resource utilization, process consumption, or host discovery. Also use when building timeseries queries for host metrics that feed into analytical workflows like anomaly detection, forecasting, or seasonality analysis. Trigger: "show hosts", "CPU usage", "memory utilization", "disk space", "high CPU", "host with most free disk", "top hosts by CPU", "top processes by memory", "Linux hosts in AWS", "what databases are running", "infrastructure costs by cost center", "hosts running EOL Java", "container monitoring", "listening ports", "process resource consumption", "CPU forecast", "memory anomaly", "host seasonality". Do NOT use for explaining existing queries, product documentation questions, Kubernetes pod/workload queries (use dt-obs-kubernetes), AWS cloud resource inventory (use dt-obs-aws), or service-level metrics (use dt-obs-services).

DAVIS problem analysis including root cause identification, impact assessment, and correlation with other telemetry. Use when querying or investigating detected problems. Trigger: "active problems", "root cause analysis", "problem impact", "affected users", "list problems", "P-12345 details", "recurring problems", "problem history", "problem trending", "blast radius", "which entity caused the problem", "problems affecting Kubernetes", "problems by service". Do NOT use for explaining existing queries, product documentation questions, generic log searching, distributed tracing, or host-level resource monitoring.

Azure cloud resources including VMs, VMSS, SQL Database, Storage, AKS, App Service, Functions, VNet networking, load balancers, Event Hubs, Container Apps, and Key Vault. Monitor Azure infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across subscriptions and resource groups.

GCP cloud resources including Compute Engine, GKE, Cloud Run, Pub/Sub, VPC networking, DNS, IAM, Secret Manager, and monitoring. Monitor GCP infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across projects and folders.

Log querying, filtering, pattern analysis, and error rate calculation. Use when searching application or infrastructure logs, analyzing error patterns, or correlating log data. Trigger: "show error logs", "search logs for keyword", "log error rate", "recent errors", "logs from last hour", "find log entries", "top error messages", "log patterns", "parse JSON logs", "logs by process group", "log trends over time", "log entry counts per minute". Do NOT use for explaining existing queries, product documentation questions, distributed tracing or span analysis (use dt-obs-tracing).

Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.

Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. Trigger: "service response time", "error rate", "throughput", "SLA compliance", "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).

Distributed traces, spans, service dependencies, and request flow analysis. Use when investigating span-level details, failures, performance bottlenecks, or trace correlation. Trigger: "trace analysis", "slow requests", "failed spans", "service dependencies", "distributed trace", "span details", "HTTP status codes in traces", "database query spans", "messaging spans", "gRPC calls", "Lambda cold starts", "trace ID lookup", "exception analysis", "correlate logs and traces", "request attributes". Do NOT use for explaining existing queries, product documentation or configuration questions, service-level RED metrics (use dt-obs-services), log searching (use dt-obs-logs), or problem analysis (use dt-obs-problems).